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saideep-arikontham/twitter-roberta-base-sentiment-latest-biden-stance-1

sourceHugging Faceupdated 2y agoView on Hugging Face
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twitter-roberta-base-sentiment-latest-biden-stance-1

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.4037
  • —Accuracy: {'accuracy': 0.5688073394495413}
  • —Precision: {'precision': 0.5540838852097131}
  • —Recall: {'recall': 0.6640211640211641}
  • —F1 Score: {'f1': 0.6040914560770156}

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 0.001
  • —trainbatchsize: 4
  • —evalbatchsize: 4
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 10

Training results

Training LossEpochStepValidation LossAccuracyPrecisionRecallF1 Score
0.43391.036000.4173{'accuracy': 0.8925}{'precision': 0.857630979498861}{'recall': 0.94125}{'f1': 0.8974970202622169}
0.38482.072000.5757{'accuracy': 0.854375}{'precision': 0.9341500765696784}{'recall': 0.7625}{'f1': 0.8396421197522368}
0.40943.0108000.3543{'accuracy': 0.904375}{'precision': 0.8655367231638418}{'recall': 0.9575}{'f1': 0.9091988130563798}
0.39374.0144000.2576{'accuracy': 0.91125}{'precision': 0.9092039800995025}{'recall': 0.91375}{'f1': 0.9114713216957606}
0.34015.0180000.2671{'accuracy': 0.91625}{'precision': 0.9291237113402062}{'recall': 0.90125}{'f1': 0.9149746192893401}
0.3526.0216000.2429{'accuracy': 0.91875}{'precision': 0.9294871794871795}{'recall': 0.90625}{'f1': 0.9177215189873418}
0.28837.0252000.2857{'accuracy': 0.915625}{'precision': 0.917189460476788}{'recall': 0.91375}{'f1': 0.915466499686913}
0.28948.0288000.2270{'accuracy': 0.92375}{'precision': 0.9302030456852792}{'recall': 0.91625}{'f1': 0.9231738035264484}
0.2829.0324000.2518{'accuracy': 0.92}{'precision': 0.9189526184538653}{'recall': 0.92125}{'f1': 0.920099875156055}
0.248510.0360000.2351{'accuracy': 0.92375}{'precision': 0.9269521410579346}{'recall': 0.92}{'f1': 0.9234629861982434}

Framework versions

  • —PEFT 0.10.0
  • —Transformers 4.38.2
  • —Pytorch 2.2.1
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2